Open Inference Networks: Democratic Access to Intelligence

Owning model weights means little if you cannot run them. Open inference is about where the computation happens. Running models locally works well in 2026. A single consumer GPU or a high-memory desktop runs 8B to 30B models at chat speed. Pooling many consumer devices to run one huge model mostly does not work over normal networks. It adds memory, not speed. Petals proved the peer-to-peer idea is possible. Its own best-case figure is about 6 tokens per second for a 70B model. Token-incentive networks such as Bittensor pay people to supply inference. They also bring validator concentration, su